In general, a vision system is provided to inspection equipment developed to automatically, rapidly and correctly perform various visual inspections on an outward appearance of an inspection subject, which have depended on human eyesight, so as to shoot and collect digital images of the inspection subject and transfer the collected images to a processing system having a quality determining function.
Such a vision system is provided with a lighting device for irradiating predetermined light to an inspection subject and a camera for photographing the inspection subject to generate a digital image. Here, instead of a high-priced color camera, a monochrome camera is typically used as the camera.
The lighting device may be a monochromatic lighting device. However, as disclosed in Korean Patent Application Laid-open Publication No. 2006-0027225, controllable color lighting has recently been widely applied to vision systems such as outward appearance inspection equipment for an LCD in order to more effectively detect a surface defect of an inspection subject.
However, a correlation between the quality of a monochromatic image shot by a monochrome camera and color lighting conditions is not clear. Therefore, an operator should manually find and set optimal color lighting conditions. However, this method is not only complex but also subjective since whether found lighting conditions are optimal is determined depending on eyesight of the operator. Moreover, whenever inspection subjects are changed, such a complex setting operation should be performed again, causing inconvenience to the operator.
When various types of inspection subjects are inspected, an additional vision system may be provided for each inspection subject in order to resolve the above-mentioned inconvenience, but this method increases the cost of inspection equipment.
Therefore, in the field of a vision system to which color lighting is applied, it is an important issue to develop an optimal color lighting control method for maximizing the quality of an image shot by a monochrome camera of a vision system so that a processing system rapidly and correctly determines the quality of an inspection subject by reading the image.
Korean Patent Application Laid-open Publication No. 2011-0060194 discloses a color lighting control method in which each pair of images corresponding to 256 to the power of 3 (2563) is obtained and analyzed while gradually adjusting each color brightness of RGB color lighting, thereby finding optimal color lighting conditions.
However, this conventional color lighting control method merely achieves improvement with respect to automatic acquisition and analysis of an image, but requires a large amount of images to be acquired and analyzed. Therefore, it takes a long time to find optimal color lighting conditions, and the life of a detector of a camera is shortened due to shooting of a large amount of images.
According to the conventional color lighting control method, an optimal image is determined according to which one of images A and B that have different color lighting conditions has a larger contrast difference between an inspection region and a background region. However, in the case where a plurality of inspection regions exist, the image A may have a larger contrast difference with respect to some inspection regions, but the image B may have a larger contrast difference with respect to other inspection regions. Therefore, it may be difficult to determine an optimal image if two images which have different color lighting conditions have conflicting superiority with respect to contrast.
In order to overcome such a limitation, the contrast difference may be checked on the basis of a specific inspection region from among a plurality of inspection regions so as to determine an optimal image. However, in this case, since the optimal image is not determined in consideration of all inspection regions, the reliability of the determination is relatively low.
That is, according to the conventional color lighting control method, a criterion for determining an optimal image is ambiguous, and thus, the method is not reliable even though optimal color lighting conditions may be found.